Google Inc.

Simon Lynen

Esha D Nerurkar

Joel Hesch

Sheng Zhao

Ryan Michael Hickman

Johnny Hsienchow Lee

Brian Patrick Williams

Laurent Tu

Eric Thomas Andresen

Dongfang Zheng

Esha Nerurkar

An electronic device tracks its motion in an environment while building a three-dimensional visual representation of the environment that is used to correct drift in the tracked motion. A motion tracking module estimates poses of the electronic device based on feature descriptors corresponding to the visual appearance of spatial features of objects in the environment. A mapping module builds a three-dimensional visual representation of the environment based on a stored plurality of maps, and feature descriptors and estimated device poses received from the motion tracking module. The mapping module provides the three-dimensional visual representation of the environment to a localization module, which identifies correspondences between stored and observed feature descriptors. The localization module performs a loop closure by minimizing the discrepancies between matching feature descriptors to compute a localized pose. The localized pose corrects drift in the estimated pose generated by the motion tracking module.

System and method for concurrent odometry and mapping

An electronic device merges a plurality of maps, or area description files (ADFs), by representing relationships among ADFs in an undirected graph, with vertices representing maps and edges representing transformations between maps. As the electronic device generates new ADFs, the electronic device merges each new ADF to a stored collection of ADFs by adding each new ADF as a vertex and transformations between the new ADF and the collection of ADFs as edges in the undirected graph. In this way, the map merger can use the undirected graph to more accurately represent the relations between any two maps, allowing more efficient merger of new maps to a previously stored collection of maps, and allowing for the development of more flexible and efficient algorithms for manipulating the merged maps.

System and method for merging maps

The present disclosure provides systems and methods that allow a first user to anchor a virtual object to a physical location and a second user to view the virtual object at the physical location. In particular, aspects of the present disclosure are directed to workflows, application programming interfaces ('APIs'), and computing system infrastructure that enable a first computing device to generate an ad hoc mapping of its physical surroundings (e.g., based on sensor data collected by the first device) and to position and anchor a virtual object at a physical location within such mapping. Data descriptive of the mapping and virtual object can be stored in a cloud database and can then be used by or for a second device to render the virtual object at the location of the anchor.

Systems and methods for anchoring virtual objects to physical locations

An electronic device reduces localization data based on feature characteristics identified from the data. Based on the feature characteristics, a quality value can be assigned to each identified feature, indicating the likelihood that the data associated with the feature will be useful in mapping a local environment of the electronic device. The localization data is reduced by removing data associated with features have a low quality value, and the reduced localization data is used to map the local environment of the device by locating features identified from the reduced localization data in a frame of reference for the electronic device.

Managing feature data for environment mapping on an electronic device

A computing system includes a network interface, a first datastore, a second datastore, and a merge module. The merge module is to receive a set of one or more area description files from a set of one or more first mobile devices. Each area description file represents a point cloud of spatial features detected by a corresponding first mobile device at an area. The computing system further includes a localization module and a query module. The localization generation module is to generate a localization area description file for the area from the set of one or more area description files and to store the localization area description file in the second datastore. The localization area description file represents a point cloud of spatial features for the area. The query module is to provide the localization area description file to a second mobile device via the network interface.

Crowd-sourced creation and updating of area description file for mobile device localization

Methods and systems for determining estimation of motion of a device are provided. An example method includes receiving data from an inertial measurement unit (IMU) of a device and receiving images from a camera of the device for a sliding time window. The method also includes determining an IMU estimation of motion of the device based on the data from the IMU, and a camera estimation of motion of the device based on feature tracking in the images. The method includes, based on the IMU estimation and the camera estimation having a difference more than a threshold amount, determining one or more of a position or a velocity of the device for the sliding time window, and determining an overall estimation of motion of the device as supported by the data from the IMU and the position or velocity of the device.

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Zurich, Switzerland

Simon Lynen